A biological marker model for predicting disease transitions

For patients with chronic myelogenous leukemia (CML), the effect of elevated blood levels of adenosine deaminase (ADA) is studied as a marker for transitions from stable disease to blast crisis and then to death. Data in the form of snapshots over time, with day, state of disease, and ADA level, are analyzed for 55 patients. A simple three-state Markov model with one-way transition probabilities dependent on ADA is used to determine if the marker has a significant effect on the prediction of changes from stable disease to blast crisis.     

A metabolomics-based approach for predicting stages of chronic kidney disease

Chronic kidney disease (CKD) is a major epidemiologic problem and a risk factor for cardiovascular events and cerebrovascular accidents. Because CKD shows irreversible progression, early diagnosis is desirable. Renal function can be evaluated by measuring creatinine-based estimated glomerular filtration rate (eGFR). This method, however, has low sensitivity during early phases of CKD. Cystatin C (CysC) may be a more sensitive predictor. Using a metabolomic method, we previously identified metabolites in CKD and hemodialysis patients. To develop a new index of renal hypofunction, plasma samples were collected from volunteers with and without CKD and metabolite concentrations were assayed by quantitative liquid chromatography/mass spectrometry. These results were used to construct a multivariate regression equation for an inverse of CysC-based eGFR, with eGFR and CKD stage calculated from concentrations of blood metabolites. This equation was able to predict CKD stages with 81.3% accuracy (range, 73.9–87.0% during 20 repeats). This procedure may become a novel method of identifying patients with early-stage CKD.     

Accuracy of predicting the genetic risk of disease using a genome-wide approach

Background

The prediction of the genetic disease risk of an individual is a powerful public health tool. While predicting risk has been successful in diseases which follow simple Mendelian inheritance, it has proven challenging in complex diseases for which a large number of loci contribute to the genetic variance. The large numbers of single nucleotide polymorphisms now available provide new opportunities for predicting genetic risk of complex diseases with high accuracy.

Methodology/Principal Findings

We have derived simple deterministic formulae to predict the accuracy of predicted genetic risk from population or case control studies using a genome-wide approach and assuming a dichotomous disease phenotype with an underlying continuous liability. We show that the prediction equations are special cases of the more general problem of predicting the accuracy of estimates of genetic values of a continuous phenotype. Our predictive equations are responsive to all parameters that affect accuracy and they are independent of allele frequency and effect distributions. Deterministic prediction errors when tested by simulation were generally small. The common link among the expressions for accuracy is that they are best summarized as the product of the ratio of number of phenotypic records per number of risk loci and the observed heritability.

Conclusions/Significance

This study advances the understanding of the relative power of case control and population studies of disease. The predictions represent an upper bound of accuracy which may be achievable with improved effect estimation methods. The formulae derived will help researchers determine an appropriate sample size to attain a certain accuracy when predicting genetic risk.     

A training primer for Institutional Officials

The laws and policies governing the care and use of animals in research in the US require institutions to establish training programs to assure that personnel are qualified for their roles in animal care and use programs. Few programs define specific training requirements for the Institutional Official (IO), one of the most important roles in an animal care program. In some cases, IOs may have little or no experience in biomedical science. In this article, the author provides an overview of the IO's role in an animal care and use program as defined by US government laws and policies for use in training IOs and chief executive officers. The author outlines the key responsibilities of the IO in an animal care program, the implications of noncompliance with federal requirements and some of the pitfalls in program design.     

A bioinformatics method for predicting long noncoding RNAs associated with vascular disease

Long noncoding RNAs (lncRNAs) play important roles in human diseases including vascular disease. Given the large number of lncRNAs, however, whether the majority of them are associated with vascular disease remains unknown. For this purpose, here we present a genomic location based bioinformatics method to predict the lncRNAs associated with vascular disease. We applied the presented method to globally screen the human lncRNAs potentially involved in vascular disease. As a result, we predicted 3043 putative vascular disease associated lncRNAs. To test the accuracy of the method, we selected 10 lncRNAs predicted to be implicated in proliferation and migration of vascular smooth muscle cells (VSMCs) for further experimental validation. The results confirmed that eight of the 10 lncRNAs (80%) are validated. This result suggests that the presented method has a reliable prediction performance. Finally, the presented bioinformatics method and the predicted vascular disease associated lncRNAs together may provide helps for not only better understanding of the roles of lncRNAs in vascular disease but also the identification of novel molecules for the diagnosis and therapy of vascular disease.     

A primer in epidemiologic methodology

Epidemiology is defined as the study of the distribution and determinants of disease within populations. In addition to the requirements for disease surveillance, epidemiologic methods have numerous applications in laboratory animal science and can reveal important insights into the multifactoral mechanisms of disease, thereby aiding in the design of optimized intervention strategies. Observational approaches to data collection can be used to quantify the role of causal factors under natural circumstances, complementing the value of experimental studies in this field. The meaning and appropriate use of standard measures of disease frequency and exposure-disease relationships are reviewed, along with explanations of bias and confounding. Recommendations for reporting the methods and findings from this type of work in comparative medicine literature are presented. Aspects of model-based approaches to data analysis are introduced, offering further opportunities for gaining needed information from epidemiologic study of problems in laboratory animal medicine and management.     

A universal procedure for primer labelling of amplicons.

Detection and visualisation of nucleic acids is integral to genome analyses. Exponential amplification procedures have provided the means for the manipulation of nucleic acid sequences, which were otherwise inaccessible. We describe the development and application of a universal method for the labelling of any PCR product using a single end-labelled primer. Amplification was performed in a single reaction with the resulting amplicon labelled to a high specific activity. The method was adapted to a wide range of PCRs and significantly reduced the expense of such analyses.     

The diffusion of new genetic tests for predicting disease.

This paper examines the pathways by which new genetic tests will become available to the public. In view of the scarcity of genetic specialists, the pathway is likely to involve primary care physicians. Other pathways entail state-mandated testing, community-based programs, or testing by laboratories without much involvement of primary care physicians. When testing does become available the destination will be either family-centered testing or population-oriented screening. The deterrent to screening will not be the inability to detect disease-causing mutations but the costs and attitudes of providers and the public. When tests are provided primarily to provide information about risks to future children, some people will oppose screening on religious or moral grounds. When there are no inexpensive treatments, some will fear that insurance companies and employers will use tests to deny them health care coverage. Some may not want to know their risks for disorders about which little can be done. For common, multifactorial disorders, genetic tests will have low predictive value. Because of these problems, the decision to be tested, regardless of the destination, requires that testees be fully informed and consent to testing. When acceptance rates are low, screening is less likely to be cost-effective; family-centered testing becomes the default destination.     

Biologically-generated primer for PCR: PCR primer of unknown sequence.

We describe a method for producing specific PCR primers directly from PCR product, bypassing the usual need to know the primer sequence. Lack of abundance of primers derived from a PCR product is compensated for by the incorporation of an arbitrary 5'TAG sequence which acts as a surrogate template target for the bulk amplification phase. We use the technique to amplify clonospecific rearranged immunoglobulin genes, which have applications as markers of lymphoid neoplasms for tracing the success of therapy. The principle may have wider application wherever conserved and variable regions of DNA are juxtaposed.